An efficient user interface based on maximizing shared information

Abstract

In designing systems with a human‐computer interface with a minimum number of interactions, there are two issues to consider: the determination of a proper sequence of questions by the user, and proper termination by the computer system, based on previous instructions. In short, these issues are those of feature selection ordering and a stopping rule for pattern recognition processes. Conventional treatments of these problems have been investigated from the viewpoint of an average error rate. When the number of patterns is large, however, and the number of instructions to be terminated is large, from the point of view of user interface efficiency, and the average error rate is not an effective indicator at the intermediate stage. In this paper, a new method is proposed for determining feature selection ordering and a stopping rule which focuses on the remaining patterns at each stage, and which maximizes the value of mutual information between the user's responses and the required pattern. Important properties associated with this scheme have been demonstrated while evaluating its performance via computer simulation. One is that the average information gain at each stage decreases monotonically, and another is that this scheme produces the minimum error rate.

abstract = "In designing systems with a human‐computer interface with a minimum number of interactions, there are two issues to consider: the determination of a proper sequence of questions by the user, and proper termination by the computer system, based on previous instructions. In short, these issues are those of feature selection ordering and a stopping rule for pattern recognition processes. Conventional treatments of these problems have been investigated from the viewpoint of an average error rate. When the number of patterns is large, however, and the number of instructions to be terminated is large, from the point of view of user interface efficiency, and the average error rate is not an effective indicator at the intermediate stage. In this paper, a new method is proposed for determining feature selection ordering and a stopping rule which focuses on the remaining patterns at each stage, and which maximizes the value of mutual information between the user's responses and the required pattern. Important properties associated with this scheme have been demonstrated while evaluating its performance via computer simulation. One is that the average information gain at each stage decreases monotonically, and another is that this scheme produces the minimum error rate.",

N2 - In designing systems with a human‐computer interface with a minimum number of interactions, there are two issues to consider: the determination of a proper sequence of questions by the user, and proper termination by the computer system, based on previous instructions. In short, these issues are those of feature selection ordering and a stopping rule for pattern recognition processes. Conventional treatments of these problems have been investigated from the viewpoint of an average error rate. When the number of patterns is large, however, and the number of instructions to be terminated is large, from the point of view of user interface efficiency, and the average error rate is not an effective indicator at the intermediate stage. In this paper, a new method is proposed for determining feature selection ordering and a stopping rule which focuses on the remaining patterns at each stage, and which maximizes the value of mutual information between the user's responses and the required pattern. Important properties associated with this scheme have been demonstrated while evaluating its performance via computer simulation. One is that the average information gain at each stage decreases monotonically, and another is that this scheme produces the minimum error rate.

AB - In designing systems with a human‐computer interface with a minimum number of interactions, there are two issues to consider: the determination of a proper sequence of questions by the user, and proper termination by the computer system, based on previous instructions. In short, these issues are those of feature selection ordering and a stopping rule for pattern recognition processes. Conventional treatments of these problems have been investigated from the viewpoint of an average error rate. When the number of patterns is large, however, and the number of instructions to be terminated is large, from the point of view of user interface efficiency, and the average error rate is not an effective indicator at the intermediate stage. In this paper, a new method is proposed for determining feature selection ordering and a stopping rule which focuses on the remaining patterns at each stage, and which maximizes the value of mutual information between the user's responses and the required pattern. Important properties associated with this scheme have been demonstrated while evaluating its performance via computer simulation. One is that the average information gain at each stage decreases monotonically, and another is that this scheme produces the minimum error rate.